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*                			For Vision Open Statistical Models											*
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* Copyright (C):	2006~2011 by JIA Pei, all rights reserved.											*
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*					1) P. JIA, 2D Statistical Models, Technical Report of Vision Open Working Group,	*
*					2st Edition, October 21, 2010. 														*
*					http://www.visionopen.com/members/jiapei/publications/pei_sm2dreport2010.pdf		*
* 					2) P. JIA. Audio-visual based HMI for an Intelligent Wheelchair. PhD thesis,		*
* 					University of Essex, February, 2011.												*
* 					http://www.visionopen.com/members/jiapei/publications/pei_phdthesis2010.pdf			*
*					3) T. Cootes and C. Taylor. Statistical models of appearance for computer vision.	*
*					Technical report, Imaging Science and Biomedical Engineering, University of 		*
*					Manchester, March 8, 2004.															*
*					http://www.isbe.man.ac.uk/~bim/Models/app_models.pdf								*
*					4) I. Matthews and S. Baker. Active appearance models revisited. International 		*
*					Journal of Computer Vision, 60(2):135–164, November 2004.							*
*					http://www.ri.cmu.edu/pub_files/pub4/matthews_iain_2004_2/matthews_iain_2004_2.pdf	*
*					5) M. B. Stegmann, Active Appearance Models: Theory, Extensions and Cases,			*
*					http://www2.imm.dtu.dk/~aam/main/, 2000												*
* 																										*
* Version:          0.3.2                                                     							*
* Author:           JIA Pei                                                 							*
* Contact:          jp4work@gmail.com                                       							*
* URL:              http://www.visionopen.com                               							*
* Create Date:      2010-11-04                                             								*
* Revise Date:      2010-08-04                                             								*
********************************************************************************************************/

#include "VO_Gabor.h"


VO_Gabor::VO_Gabor()
{
	this->init();
}


/** Initialization */
void VO_Gabor::init()
{
}


VO_Gabor::~VO_Gabor()
{
}


/**
 * @author     	JIA Pei
 * @version    	2010-03-05
 * @brief      	Prepare a Gabor Kernel
 * @param		nstds			Input	-- how many (n) standard deviations?
 * @param		lamda			Input	-- the wavelength of the cosine factor
 * @param		theta			Input	-- the orientation of the normal to the parallel stripes of a Gabor function
 * @param		psi				Input	-- the phase offset
 * @param		sigma			Input	-- the sigma of the Gaussian envelope
 * @param		gamma 			Input	-- the spatial aspect ratio, and specifies the ellipticity of the support of the Gabor function
 * @return		void
 * @ref			http://en.wikipedia.org/wiki/Gabor_filter
*/
void VO_Gabor::VO_PrepareGaborKernel( unsigned int nstds,
										float lambda,
										float theta,
										float psi,
										float sigma,
										float gamma)
{
	float sigma_x = sigma;
	float sigma_y = sigma/gamma;
	float x_theta, y_theta;

	// Bounding box	-- compute the kernel size
	int xmax = ceil( max(1.0f, max(fabs((float)nstds*sigma_x*cos(theta)),fabs((float)nstds*sigma_y*sin(theta))) ) );
	int ymax = ceil( max(1.0f, max(fabs((float)nstds*sigma_x*sin(theta)),fabs((float)nstds*sigma_y*cos(theta))) ) );
	int xmin = -xmax;
	int ymin = -ymax;

	this->m_VOWindowFunc->m_MatWindowedKernel	= Mat_<float>::zeros(2*ymax+1, 2*xmax+1);

	for(int y = ymin; y <= ymax; y++)
	{
		for(int x = xmin; x <= xmax; x++)
		{
			x_theta=x*cos(theta)+y*sin(theta);
			y_theta=-x*sin(theta)+y*cos(theta);
			this->m_VOWindowFunc->m_MatWindowedKernel(y - ymin, x - xmin) 
				= exp(-.5f*(pow(x_theta,2.0f)/pow(sigma_x,2.0f)+pow(y_theta,2.0f)/pow(sigma_y,2.0f)))
					*cos(2.0*CV_PI/lambda*x_theta+psi);
		}
	}

	// take record finally.
	this->m_fNStds		= nstds;
	this->m_fLamda		= lambda;
	this->m_fTheta		= theta;
	this->m_fPSI		= psi;
	this->m_fSigma		= sigma;
	this->m_fGamma		= gamma;
}


/**
 * @brief		Gabor filtering
 * @ref			http://en.wikipedia.org/wiki/Gabor_filter
 */
float VO_Gabor::VO_GaborFiltering(const Mat_<float>& iImg)
{
	return iImg.dot(this->m_VOWindowFunc->m_MatWindowedKernel);
}